Class Summary |
BoxPlot |
BoxPlot class |
Cast |
Static Class for casting Object arrays to their corresponding primitive type. |
Comparison |
Contains a number of methods for comparing more than one dataset
against each other. |
Comparison.TTest |
Methods related to comparing two populations. |
Correlation |
Contains utilities related to computing covariances, as well as linear and rank correlation. |
Correlation.Significance |
Contains methods used to compute the significance, or pvalue of the input correlations. |
Correlation.Weighted |
Contains methods related to computing the correlation and covariance of weighted
datasets. |
CorrelationPlot |
Takes in a matrix and plots the data in each of the columns versus
each other. |
Descriptive |
Basic descriptive statistics class for exploratory data analysis. |
Descriptive.Mean |
Contains methods for computing the arithmetic, geometric, harmonic, trimmed, and winsorized
means (among others). |
Descriptive.Pooled |
Class for computing the pooled mean and variance of data sequences |
Descriptive.Sum |
Methods for computing various different sums of datasets such as sum of inversions,
logs, products, power deviations, squares, etc. |
Descriptive.Weighted |
Contains methods related to weighted datasets. |
Distance |
Contains methods for computing various "distance" metrics for multidimensional scaling. |
Eigenvalue |
Eigenvalues and eigenvectors of a real matrix. |
Find |
Static class for finding indices in an array corresponding to a given value/object. |
Frequency |
Class for getting the frequency distribution, cumulative frequency distribution, and other
distribution-related parameters of a given array of floats or ints. |
Gamma |
Gamma and Beta functions. |
Linear |
Contains methods related to determining the linear linear
relationship between two datasets (of equal arrays) such as the
best-fit linear line parameters, box-cox transformations, etc. |
Linear.BoxCox |
Contains methods related to the Box-Cox transformation of a data set; useful in
determining the best transformation that will yield the best method for converting
a monotonic, non-linear relationship between x and y into
a linear one. |
Linear.Significance |
Contains methods used to compute the significance, or pvalue of the input correlations. |
Linear.StdErr |
Contains methods related to computing the standard errors of the residuals, slope and intercept
associated with the best-fit linear line. |
LU |
LU Decomposition. |
Mat |
Static class for performing some basic matrix operations. |
MDS |
Contains methods for performing but classical and non-classical multidimensional scaling. |
NaNs |
Contains various methods for dealing with NaNs in your data. |
Normality |
Contains various utilities for checking if the dataset comes from a normal distribution. |
Normality.Dago |
Methods for computing the skewnewss, kurtosis, and D'Agostino-Peasrson K^2 "omnibus" test-statistics (that
combine the former two), and accompanying significance (or p-values)
for testing the underlying population normality. |
OneWayAnova |
Computes the one-way ANOVA p-value to test the equality of two or more sample
means by analyzing the sample variances using the test statistic
F = variance between samples / variance within samples . |
Polynomial |
Static Class for casting one variable type to another. |
Probability |
Cumulative distribution functions and corresponding inverses of certain probability distributions. |
QR |
QR Decomposition. |
Rank |
Ranking based on the natural ordering on floats for a sequence of data that may also
contain NaNs. |
ScatterPlot |
A simple class to plot x vs y data as a
scatter plot. |
Sorting |
Class for getting the array of indices that can be used to sort the array in ascending or
descending order. |
SubPlot |
Convenient class for drawing multiple scatter plots. |
SVD |
Singular Value Decomposition. |
Unique |
Class for getting and storing an unsorted array's unique elements,
the indices of these elements, and the number of times the elements occur. |
Visuals |
Visuals is the parent class behind most of the other plotting classes. |